Project Summary Reward based learning can have a dramatic impact on behavior. Learning to associate particular stimuli in the environment with reward can help guide our attention to potentially rewarding outcomes. However, this can also be costly when reward associated stimuli distract us from task-relevant information. The costs of reward-driven distraction include risks to health. Reward learning has been implicated in addiction where it is thought that reward learning creates long-term persistent attention biases towards the substance of addiction and the environmental cues associated with that substance. The energy cost of resisting reward-driven behaviors, as well as the degree of fatigue, may affect the motivation to resist. It is possible that under conditions of fatigue the energy cost of resisting would be higher and thus the motivation to resist is reduced. It has even been suggested that fatigue is a ?universal risk factor? for relapse in addictions, but this hypothesis has not been tested directly, and the mechanism for the predictive relationship between fatigue and relapse has not been identified. We propose that fatigue facilitates relapse by exacerbating automatic attention capture by reward-associated cues, and that reward-driven capture is facilitated by fatigue more generally, outside the context of addiction. However, there is yet no evidence, either in humans or animal models, of how fatigue affects behaviors learned via reward. We will test three specific hypotheses: 1) Physical fatigue exacerbates persistent attention capture by formerly reward-associated visual features; 2) Physical fatigue exacerbates persistent attention capture by reward-associated visual features by impairing cognitive control; and 3) Physical fatigue uniquely exacerbates attention capture by reward-associated features. This work involves integrating two different lines of basic research from our lab, one on reward- driven attention and one on physical fatigue. We will use behavioral performance, EEG-fMRI, and cutting- edge multivariate analytical tools to elucidate the neural mechanisms of reward-driven attention that are modulated by fatigue states. The proposed work would provide evidence that physical fatigue uniquely modulates the persistent effects of reward learning on behavior, and that this effect is due to decreased cognitive control. This work would be the first to show that the state of an individual modulates reward-driven attention capture. This insight contributes to our understanding of the fundamental mechanisms for the effects of reward learning on attention, as well as to ways to mitigate the costly effects of reward-driven capture.